8 citations · 25 across the 28 of their papers we have counts for
8 papers · 1 filter
Modeling Nonlinear Oscillator Networks Using Physics-Informed Hybrid Reservoir Computing
Andrew Shannon, Conor Houghton, David Barton +1
Surrogate modeling of non-linear oscillator networks remains challenging due to discrepancies between simplified analytical models and real-world complexity. To bridge this gap, we…
Cooperation as well as learning: A commentary on 'How learning can guide evolution' by Hinton and Nowlan
Conor Houghton
According to the Baldwin Effect learning can guide evolution. This does not suppose that information about what has been learned is transferred back into the genetic code: in the B…
Residual Stream Analysis with Multi-Layer SAEs
Tim Lawson, Lucy Farnik, Conor Houghton +1
Sparse autoencoders (SAEs) are a promising approach to interpreting the internal representations of transformer language models. However, SAEs are usually trained separately on eac…
Investigating the Timescales of Language Processing with EEG and Language Models
Davide Turco, Conor Houghton
This study explores the temporal dynamics of language processing by examining the alignment between word representations from a pre-trained transformer-based language model, and EE…
Modeling language contact with the Iterated Learning Model
Seth Bullock, Conor Houghton
Contact between languages has the potential to transmit vocabulary and other language features; however, this does not always happen. Here, an iterated learning model is used to ex…
An iterated learning model of language change that mixes supervised and unsupervised learning
Jack Bunyan, Seth Bullock, Conor Houghton
The iterated learning model is an agent model which simulates the transmission of of language from generation to generation. It is used to study how the language adapts to pressure…